Instructions to use aajrami/bert-ascii-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aajrami/bert-ascii-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="aajrami/bert-ascii-medium")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("aajrami/bert-ascii-medium") model = AutoModel.from_pretrained("aajrami/bert-ascii-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 127e802986e067648a81f11fe049fd015c30671f36c4eb40c62b90ecdbf0504f
- Size of remote file:
- 206 MB
- SHA256:
- e8fd955715645bf0f129623a00b8aff8478b9ca1389ae47108052a023ba74cb5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.